Here’s just a fraction of what you can do with linear algebra

math and programming and I see linear algebra applied to computer science all the time. Here’s a short list that comprises a small fraction of the things you can do with linear algebra.

series of blog posts I wrote deriving the method.

Here’s a series (still in progress) on the mathematics behind linear programming. The primary technique for solving them, called the simplex algorithm, is essentially a beefed up Gaussian elimination.

Here’s an article describing the simplest kind of error correcting code, the Hamming code.

A discrete cousin of Fourier analysis has been part of many theoretical techniques in computer science as well.

Graphics: Pretty much all graphics innovation since computers have existed have come from video games and movies. The central part of graphics is projecting a three-dimensional scene onto a two-dimensional screen. Projection is already a linear map. On top of that, rotations, scaling, and perspective are all implemented and analyzed properly using linear algebra.

a more general article showing PCA for any dataset. Here is a picture of what an “eigenface” might look like.

$Here’s just a fraction of what you can do with linear algebra$ $Here’s just a fraction of what you can do with linear algebra$

linear regression.

Here is an overview of some notions of community detection.

Here is an article proving what I just said.

Here is the first of a series of articles (in progress) doing this, and it gives you an idea of how linear algebra is the primary tool.

kinds of useful.